Modeling intermittent drying using an adaptive neuro-fuzzy inference system

Abstract

Artificial intelligence systems such as artificial neural networks (ANN) and fuzzy inference systems (FIS) are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. The advantages of a combination of ANN and FIS are obvious. This article presents the application of a hybrid neuro-fuzzy system called adaptive-network-based fuzzy inference system (ANFIS) to time dependent drying processes and is illustrated by an application to model intermittent drying of grains in a spouted bed. An introduction to the ANFIS modeling approach is also presented. The model showed good performance in terms of various statistical indices. Copyright © 2005 Taylor & Francis, Inc.